Analysts in various professions may, at times, be called upon to search relatively large collections of imagery to identify, if present, various types of relevant information (referred to herein as “a target entity” or “target entities”) in the collection of imagery. For example, medical analysts sometimes diagnose a physical impairment by searching complex imagery collections to identify one or more target entities therein that may be the cause of the physical impairment. Moreover, intelligence analysts may be called upon to search relatively complex imagery collections to identify target entities therein that may relate to various types of intelligence gathering activities.
Advancements in both image collection and storage technology presently allow for the relatively low-cost storage of large volumes of high-quality imagery. However, the cost of searching through large sets of imagery for target entities can often be substantial. Indeed, in many professions, such as intelligence gathering, effective searching may rely on the expertise of highly skilled analysts, who typically search through relatively large sequences of images in a relatively slow manner. Presently, the number of skilled analysts available to search the amount of imagery that is stored, or can potentially be stored, is in many instances insufficient.
In response to the foregoing, there has relatively recently been a focus on developing various systems and methods for triaging imagery. One of the methods that has shown promise combines electroencephalography (EEG) technology and rapid serial visualization presentation (RSVP). Various implementations of this combination have been researched and developed. For example, various researchers have experimented with a system in which users are presented, using the RSVP paradigm, a sequence of images, some of which may include particular types of target entities. During the RSVP presentation, EEG data are collected from the users. The collected EEG data are used to assign probabilities to each image. The probabilities are representative of the likelihood that an image includes a target.
Although useful in sorting a sequence of images, the above described system and method, as well as other systems and methods that employ these same technologies, do suffer certain drawbacks. For example, present systems and methods assume that the presence of a target is uniformly likely over the entirety of an image. As a consequence, areas that are less likely to include targets may be given the same weight as areas that are more likely. Additionally because each area of an image is typically viewed only once, common events, such as eye blinks, or a turn of the head, or various other momentary lapses, can increase the likelihood of missing one or more targets.
Hence, there is a need for a RSVP presentation technique that is robust to momentary lapses. There is also a need for approaches that allow a user to exploit contextual cues. The present invention addresses one or more of these needs.